Supportive Supervision in Monitoring and Evaluation with Community-based Health Staff in HIV Programs: A Case Study from Haiti
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Author(s): Marshall A, Fehringer J
Supportive supervision is a facilitative approach to supervision that promotes mentorship, joint problem-solving and communication between supervisors and supervisees. In recent years, supportive supervision has been implemented to improve routine program monitoring and evaluation (M&E). However, there is a lack of documentation on how supportive supervision has been applied to M&E at the community-level. The purpose of this research was to develop a case study that could be used as an example for other community-based programs wishing to use supportive supervision in M&E.
MEASURE Evaluation’s supportive supervision project in Haiti was selected as the case under study. Data were collected through 11 key informant interviews and four direct observations with governmental, nongovernmental, and MEASURE Evaluation staff involved in the supportive supervision project. Participants were sampled purposively. Interview topics included the project background, description of supportive supervision visits and supervision tools, outcomes of the project, and recommendations. Interview transcripts, direct observation notes, and documents were coded and analyzed using a descriptive case study framework.
Findings from interviews and direct observations suggest that the supportive supervision project was successful in improving data quality and data collection at the community-level, achieving a consistent use of tools to facilitate supervision, and providing feedback on staff performance. Participants attributed these successes to standardized data collection tools, ongoing supervision, and training. Emphasis on data use strategies and collaboration and mentoring during supportive supervision visits emerged as aspects of the project that needed improvement.
Supportive supervision is a promising approach to improve routine data collection for M&E of community-based programs. It can increase staff capacity to collect, manage, and use data and improve leadership capacity to make decisions based on collected data. By enhancing a program’s capacity to synthesize and disseminate information, it also contributes to the larger goal of health systems strengthening.
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